CTE | Seeq as a system for data management

Seeq: Industrial data analysis for your production operation

Seeq is a software platform for the analysis and visualization of industrial time series data that has been specially developed for production companies in industries such as chemicals, pharmaceuticals, energy and food.

It combines powerful tools for data cleansing, modeling and machine learning with a user-friendly interface that can be used without programming knowledge. With features such as real-time dashboards, automated reports and seamless integration with existing data systems such as Historian databases (e.g. AVEVA PI) or cloud solutions, Seeq helps companies to enable more efficient processes and informed decisions.

Data management? No problem!

Book a non-binding consultation with Patric Sumlak, OT Solutions Engineer.

Seeq helps you to analyze your production data efficiently, optimize processes and make data-based decisions faster. Seeq supports cross-team collaboration and provides real-time insights to proactively solve challenges.

Your advantages with Seeq:

Ease of use: With an intuitive low/no-code interface, even users without programming skills can perform analyses, create dashboards and share insights.

Real-time insights and automation: Data can be updated automatically, enabling real-time monitoring, predictive analytics and reporting.

Seamless integration: Seeq connects easily with existing data systems such as Historian databases and cloud solutions, so that all relevant data is centrally available.

Cross-team collaboration: Interactive dashboards and reports promote collaboration in teams and enable shared use of analyses.

Possible applications :

Root cause analysis: Identify and analyze the causes of process deviations or unplanned downtimes to prevent them from recurring.

Process OptimisationUse Seeq to analyze and improve production cycles, energy consumption and efficiency.

Predict maintenance requirements: Implement predictive maintenance strategies to avoid breakdowns and maximize equipment availability.

Automated reporting: Create reports and dashboards that automatically update with new data, allowing you to make data-driven decisions in real time.

Integration of machine learning: Develop models for forecasting and optimization that can be integrated directly into existing workflows.